Papers HTR
“HTR” 태그가 달린 논문 84편 · 필터 해제
Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques
Offline Handwritten Text Recognition (HTR) systems play a crucial role in applications such as historical document digitization, automatic form processing, and biometric authentication. However, their performance is ofte…
Data AugmentationHandwritten Text RecognitionHTRSurvey+1MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning
Recent advancements in handwritten text recognition (HTR) have enabled the effective conversion of handwritten text to digital formats. However, achieving robust recognition across diverse writing styles remains challeng…
Handwritten Text RecognitionHTRImage ReconstructionMeta-LearningPreserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognition
Handwritten Text Recognition (HTR) is essential for document analysis and digitization. However, handwritten data often contains user-identifiable information, such as unique handwriting styles and personal lexicon choic…
Handwritten Text RecognitionHTRMachine UnlearningTRIDIS: A Comprehensive Medieval and Early Modern Corpus for HTR and NER
This paper introduces TRIDIS (Tria Digita Scribunt), an open-source corpus of medieval and early modern manuscripts. TRIDIS aggregates multiple legacy collections (all published under open licenses) and incorporates larg…
Handwritten Text RecognitionHTRnamed-entity-recognitionNamed Entity Recognition+3Benchmarking Large Language Models for Handwritten Text Recognition
Traditional machine learning models for Handwritten Text Recognition (HTR) rely on supervised training, requiring extensive manual annotations, and often produce errors due to the separation between layout and text proce…
BenchmarkingHandwritten Text RecognitionHTRJudge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription
Handwritten text recognition (HTR) remains a challenging task, particularly for multi-page documents where pages share common formatting and contextual features. While modern optical character recognition (OCR) engines a…
Handwritten Text RecognitionHTROptical Character RecognitionOptical Character Recognition (OCR)Handwritten Text Recognition: A Survey
Handwritten Text Recognition (HTR) has become an essential field within pattern recognition and machine learning, with applications spanning historical document preservation to modern data entry and accessibility solutio…
BenchmarkingHandwritten Text RecognitionHTRSurveyEarly evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records
We explore the ability of two LLMs -- GPT-4o and Claude Sonnet 3.5 -- to transcribe historical handwritten documents in a tabular format and compare their performance to traditional OCR/HTR systems: EasyOCR, Keras, Pytes…
HTROptical Character Recognition (OCR)HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge Distillation
Despite significant advances in deep learning, current Handwritten Text Recognition (HTR) systems struggle with the inherent complexity of historical documents, including diverse writing styles, degraded text quality, an…
Computational EfficiencyHandwritten Text RecognitionHTRKnowledge Distillation+4ResFlow: Fine-tuning Residual Optical Flow for Event-based High Temporal Resolution Motion Estimation
Event cameras hold significant promise for high-temporal-resolution (HTR) motion estimation. However, estimating event-based HTR optical flow faces two key challenges: the absence of HTR ground-truth data and the intrins…
HTRMotion EstimationOptical Flow EstimationOn the Generalization of Handwritten Text Recognition Models
Recent advances in Handwritten Text Recognition (HTR) have led to significant reductions in transcription errors on standard benchmarks under the i.i.d. assumption, thus focusing on minimizing in-distribution (ID) errors…
Domain AdaptationDomain GeneralizationHandwritten Text RecognitionHTR+1Unlocking the Archives: Using Large Language Models to Transcribe Handwritten Historical Documents
This study demonstrates that Large Language Models (LLMs) can transcribe historical handwritten documents with significantly higher accuracy than specialized Handwritten Text Recognition (HTR) software, while being faste…
Handwritten Text RecognitionHTRHespi: A pipeline for automatically detecting information from hebarium specimen sheets
Specimen associated biodiversity data are sought after for biological, environmental, climate, and conservation sciences. A rate shift is required for the extraction of data from specimen images to eliminate the bottlene…
Handwritten Text RecognitionHTRLanguage ModellingLarge Language Model+5HATFormer: Historic Handwritten Arabic Text Recognition with Transformers
Arabic handwritten text recognition (HTR) is challenging, especially for historical texts, due to diverse writing styles and the intrinsic features of Arabic script. Additionally, Arabic handwriting datasets are smaller …
DecoderHandwritten Text RecognitionHTRInformation RetrievalGeneral Detection-based Text Line Recognition
We introduce a general detection-based approach to text line recognition, be it printed (OCR) or handwritten (HTR), with Latin, Chinese, or ciphered characters. Detection-based approaches have until now been largely disc…
HTROptical Character Recognition (OCR)HTR-VT: Handwritten Text Recognition with Vision Transformer
We explore the application of Vision Transformer (ViT) for handwritten text recognition. The limited availability of labeled data in this domain poses challenges for achieving high performance solely relying on ViT. Prev…
Handwritten Text RecognitionHTRDiffusionPen: Towards Controlling the Style of Handwritten Text Generation
Handwritten Text Generation (HTG) conditioned on text and style is a challenging task due to the variability of inter-user characteristics and the unlimited combinations of characters that form new words unseen during tr…
DiversityHTRMetric LearningText GenerationRethinking HTG Evaluation: Bridging Generation and Recognition
The evaluation of generative models for natural image tasks has been extensively studied. Similar protocols and metrics are used in cases with unique particularities, such as Handwriting Generation, even if they might no…
DiversityHandwriting generationHTRMuharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition
We present the Manuscripts of Handwritten Arabic~(Muharaf) dataset, which is a machine learning dataset consisting of more than 1,600 historic handwritten page images transcribed by experts in archival Arabic. Each docum…
Handwritten Text RecognitionHTRCallico: a Versatile Open-Source Document Image Annotation Platform
This paper presents Callico, a web-based open source platform designed to simplify the annotation process in document recognition projects. The move towards data-centric AI in machine learning and deep learning underscor…
Document Layout AnalysisHTRnamed-entity-recognitionNamed Entity Recognition+1